Improved Reliability of FPGA-based PUF Identification Generator Design

Physical unclonable functions (PUFs), a form of physical security primitive, enable digital identifiers to be extracted from devices, such as field programmable gate arrays (FPGAs). Many PUF implementations have been proposed to generate these unique n -bit binary strings. However, they often offer insufficient uniqueness and reliability when implemented on FPGAs and can consume excessive resources. To address these problems, in this article we present an efficient, lightweight, and scalable PUF identification (ID) generator circuit that offers a compact design with good uniqueness and reliability properties and is specifically designed for FPGAs. A novel post-characterisation methodology is also proposed that improves the reliability of a PUF without the need for any additional hardware resources. Moreover, the proposed post-characterisation method can be generally used for any FPGA-based PUF designs. The PUF ID generator consumes 8.95% of the hardware resources of a low-cost Xilinx Spartan-6 LX9 FPGA and 0.81% of a Xilinx Artix-7 FPGA. Experimental results show good uniqueness, reliability, and uniformity with no occurrence of bit-aliasing. In particular, the reliability of the PUF is close to 100% over an environmental temperature range of 25°C to 70°C with ± 10% variation in the supply voltage. </jats:p

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency

Generation of Distal Airway Epithelium from Multipotent Human Foregut Stem Cells.

Collectively, lung diseases are one of the largest causes of premature death worldwide and represent a major focus in the field of regenerative medicine. Despite significant progress, only few stem cell platforms are currently available for cell-based therapy, disease modeling, and drug screening in the context of pulmonary disorders. Human foregut stem cells (hFSCs) represent an advantageous progenitor cell type that can be used to amplify large quantities of cells for regenerative medicine applications and can be derived from any human pluripotent stem cell line. Here, we further demonstrate the application of hFSCs by generating a near homogeneous population of early pulmonary endoderm cells coexpressing NKX2.1 and FOXP2. These progenitors are then able to form cells that are representative of distal airway epithelium that express NKX2.1, GATA6, and cystic fibrosis transmembrane conductance regulator (CFTR) and secrete SFTPC. This culture system can be applied to hFSCs carrying the CFTR mutation Δf508, enabling the development of an in vitro model for cystic fibrosis. This platform is compatible with drug screening and functional validations of small molecules, which can reverse the phenotype associated with CFTR mutation. This is the first demonstration that multipotent endoderm stem cells can differentiate not only into both liver and pancreatic cells but also into lung endoderm. Furthermore, our study establishes a new approach for the generation of functional lung cells that can be used for disease modeling as well as for drug screening and the study of lung development.This work was funded by the ERC starting grant Relieve IMDs (L.V.), the Cambridge Hospitals National Institute for Health Research Biomedical Research Center (L.V., N.R.F.H.), and the Evelyn trust (N.R.F.H.). N.A.H. is a Wellcome Trust senior clinical fellow (WT088566, WT097820). F.S. has been funded by an ACT Clinical Research Training Fellowship and a joint Sparks-MRC Clinical Research Training Fellowship. C.-P.S. is funded by the Children's Liver Diseases Foundation.This is the final version of the article. It first appeared from Mary Ann Liebert Publishers via http://dx.doi.org/10.1089/scd.2014.051

TEAD and YAP regulate the enhancer network of human embryonic pancreatic progenitors

PMCID: PMC4434585.-- et al.The genomic regulatory programmes that underlie human organogenesis are poorly understood. Pancreas development, in particular, has pivotal implications for pancreatic regeneration, cancer and diabetes. We have now characterized the regulatory landscape of embryonic multipotent progenitor cells that give rise to all pancreatic epithelial lineages. Using human embryonic pancreas and embryonic-stem-cell-derived progenitors we identify stage-specific transcripts and associated enhancers, many of which are co-occupied by transcription factors that are essential for pancreas development. We further show that TEAD1, a Hippo signalling effector, is an integral component of the transcription factor combinatorial code of pancreatic progenitor enhancers. TEAD and its coactivator YAP activate key pancreatic signalling mediators and transcription factors, and regulate the expansion of pancreatic progenitors. This work therefore uncovers a central role for TEAD and YAP as signal-responsive regulators of multipotent pancreatic progenitors, and provides a resource for the study of embryonic development of the human pancreas.The research was supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre. Work was funded by grants from the Ministerio de Economía y Competitividad (CB07/08/0021, SAF2011-27086, PLE2009-0162 to J.F., BFU2013-41322-P to J.L.G-S.), the Andalusian Government (BIO-396 to J.L.G-S.), the Wellcome Trust (WT088566 and WT097820 to N.A.H., WT101033 to J.F.), the Manchester Biomedical Research Centre, ERC advanced starting grant IMDs (C.H-H.C. and L.V.) and the Cambridge Hospitals National Institute for Health Research Biomedical Research Centre (L.V.). R.E.J. is a Medical Research Council clinical training fellow. The authors are grateful to C. Wright (Vanderbilt University) for zebrafish Pdx1 antiserum, J. Postlethwait (Purdue University) for a Sox9b clone, H. Sasaki (Kumamoto University) for a TEAD–EnR clone, C. Vinod and L. Abi for research nurse assistance, and clinical colleagues at Central Manchester University Hospitals NHS Foundation Trust. The authors thank J. Garcia-Hurtado for technical assistance (IDIBAPS).Peer Reviewe

The window period of NEUROGENIN3 during human gestation

The basic helix-loop-helix transcription factor, NEUROG3, is critical in causing endocrine commitment from a progenitor cell population in the developing pancreas. In human, NEUROG3 has been detected from 8 weeks postconception (wpc). However, the profile of its production and when it ceases to be detected is unknown. In this study we have defined the profile of NEUROG3 detection in the developing pancreas to give insight into when NEUROG3- dependent endocrine commitment is possible in the human fetus. Immunohistochemistry allowed counting of cells with positively stained nuclei from 7 wpc through to term. mRNA was also isolated from sections of human fetal pancreas and NEUROG3 transcription analyzed by quantitative reverse transcription and polymerase chain reaction. NEUROG3 was detected as expected at 8 wpc. The number of NEUROG3-positive cells increased to peak levels between 10 wpc and 14 wpc. It declined at and after 18 wpc such that it was not detected in human fetal pancreas at 35-41 wpc. Analysis of NEUROG3 transcription corroborated this profile by demonstrating very low levels of transcript at 35-41 wpc, more than 10-fold lower than levels at 12-16 wpc. These data define the appearance, peak and subsequent disappearance of the critical transcription factor, NEUROG3, in human fetal pancreas for the first time. By inference, the window for pancreatic endocrine differentiation via NEUROG3 action opens at 8 wpc and closes between 21 and 35 wpc

Laser Capture and Deep Sequencing Reveals the Transcriptomic Programmes Regulating the Onset of Pancreas and Liver Differentiation in Human Embryos.

To interrogate the alternative fates of pancreas and liver in the earliest stages of human organogenesis, we developed laser capture, RNA amplification, and computational analysis of deep sequencing. Pancreas-enriched gene expression was less conserved between human and mouse than for liver. The dorsal pancreatic bud was enriched for components of Notch, Wnt, BMP, and FGF signaling, almost all genes known to cause pancreatic agenesis or hypoplasia, and over 30 unexplored transcription factors. SOX9 and RORA were imputed as key regulators in pancreas compared with EP300, HNF4A, and FOXA family members in liver. Analyses implied that current in vitro human stem cell differentiation follows a dorsal rather than a ventral pancreatic program and pointed to additional factors for hepatic differentiation. In summary, we provide the transcriptional codes regulating the start of human liver and pancreas development to facilitate stem cell research and clinical interpretation without inter-species extrapolation.This project received support from the UK Medical Research Council (MRC) (R.E.J. was a clinical research training fellow; additional funding from MR/L009986/1 to N.B. and N.A.H.; and MR/J003352/1 to K.P.H.), the Academy of Medical Sciences (supported by Wellcome Trust, MRC, British Heart Foundation, Arthritis Research UK, the Royal College of Physicians and Diabetes UK) (R.E.J.), the Society for Endocrinology (R.E.J.), the Wellcome Trust (N.A.H. was a senior fellow in clinical science, 088566; additional support from grant 105610/Z/14/Z), and the British Council and JDRF (14BX15NHBG to N.A.H.)

Heterogeneity of preferences for the benefits of environmental stewardship: a latent-class approach

Since 2005, Environmental Stewardship (ES) has been the principal agri-environment scheme for England and is the key instrument for the delivery of increased environmental benefits from agricultural landscapes. The main objective of this study is to investigate whether or not individuals' preferences for the environmental benefits associated with ES vary depending on types of landscapes within which these benefits are delivered. A latent class model is applied to data obtained from a choice experiment survey of over 1000 respondents sampled across England. The results suggest that individuals have heterogenous preferences for the benefits of ES, though different segments of the population with more homogenous preferences can be identified. In particular, higher levels of benefit are often associated with the operation of ES in landscapes close to where respondents live. This leads to the suggestion that, in order to maximise the benefits of ES, its implementation could take this result into account by encouraging greater uptake from farmers whose land is closer to large populations

Accelerating Fully Homomorphic Encryption over the Integers with Super-size Hardware Multiplier and Modular Reduction

A fully homomorphic encryption (FHE) scheme is envisioned as being a key cryptographic tool in building a secure and reliable cloud computing environment, as it allows arbitrarily evaluation of a ciphertext without revealing the plaintext. However, existing FHE implementations remain impractical due to their very high time and resource costs. Of the proposed schemes that can perform FHE to date, a scheme known as FHE over the integers has the ad-vantage of comparatively simpler theory, as well as the employment of a much shorter public key making its implementation somewhat more practical than other competing schemes. To the author’s knowledge, this paper presents the first hardware implemen-tations of encryption primitives for FHE over the integers using FPGA technol-ogy. First of all, a super-size hardware multiplier architecture utilising the Inte-ger-FFT multiplication algorithm is proposed, and a super-size hardware Barrett modular reduction module is designed incorporating the proposed multiplier. Next, two encryption primitives that are used in two schemes of FHE over the integers are designed employing the proposed super-size multiplier and modular reduction modules. Finally, the proposed designs are implemented and verified on the Xilinx Virtex-7 FPGA platform. Experimental results show that the speed improvement factors of up to 44.72 and 54.42 are available for the two FHE encryption schemes implemented in FPGA when compared to the corresponding software implementations. Meanwhile, the performance analysis shows that further improvement is speed of these FHE encryption primitives may still be possible